An Improved Nonmonotone Filter Trust Region Method for Equality Constrained Optimization

Motivated by the method of Su and Pu (2009), we present an improved nonmonotone filter trust region algorithm for solving nonlinear equality constrained optimization. In our algorithm a modified nonmonotone filter technique is proposed and the restoration phase is not needed. At every iteration, in...

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Main Author: Zhong Jin
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Abstract and Applied Analysis
Online Access:http://dx.doi.org/10.1155/2013/163487
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author Zhong Jin
author_facet Zhong Jin
author_sort Zhong Jin
collection DOAJ
description Motivated by the method of Su and Pu (2009), we present an improved nonmonotone filter trust region algorithm for solving nonlinear equality constrained optimization. In our algorithm a modified nonmonotone filter technique is proposed and the restoration phase is not needed. At every iteration, in common with the composite-step SQP methods, the step is viewed as the sum of two distinct components, a quasinormal step and a tangential step. A more relaxed accepted condition for trial step is given and a crucial criterion is weakened. Under some suitable conditions, the global convergence is established. In the end, numerical results show our method is effective.
format Article
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institution Kabale University
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spelling doaj-art-8201385d4e07407898b3f3f0f9e66b242025-08-20T03:35:24ZengWileyAbstract and Applied Analysis1085-33751687-04092013-01-01201310.1155/2013/163487163487An Improved Nonmonotone Filter Trust Region Method for Equality Constrained OptimizationZhong Jin0Department of Mathematics, Shanghai Maritime University, Shanghai 201306, ChinaMotivated by the method of Su and Pu (2009), we present an improved nonmonotone filter trust region algorithm for solving nonlinear equality constrained optimization. In our algorithm a modified nonmonotone filter technique is proposed and the restoration phase is not needed. At every iteration, in common with the composite-step SQP methods, the step is viewed as the sum of two distinct components, a quasinormal step and a tangential step. A more relaxed accepted condition for trial step is given and a crucial criterion is weakened. Under some suitable conditions, the global convergence is established. In the end, numerical results show our method is effective.http://dx.doi.org/10.1155/2013/163487
spellingShingle Zhong Jin
An Improved Nonmonotone Filter Trust Region Method for Equality Constrained Optimization
Abstract and Applied Analysis
title An Improved Nonmonotone Filter Trust Region Method for Equality Constrained Optimization
title_full An Improved Nonmonotone Filter Trust Region Method for Equality Constrained Optimization
title_fullStr An Improved Nonmonotone Filter Trust Region Method for Equality Constrained Optimization
title_full_unstemmed An Improved Nonmonotone Filter Trust Region Method for Equality Constrained Optimization
title_short An Improved Nonmonotone Filter Trust Region Method for Equality Constrained Optimization
title_sort improved nonmonotone filter trust region method for equality constrained optimization
url http://dx.doi.org/10.1155/2013/163487
work_keys_str_mv AT zhongjin animprovednonmonotonefiltertrustregionmethodforequalityconstrainedoptimization
AT zhongjin improvednonmonotonefiltertrustregionmethodforequalityconstrainedoptimization